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VARIABLE VIEWPOINT REALITY



In the foreseeable future, sporting events will be recorded in super high fidelity from hundreds or even thousands of cameras. Currently the nature of television broadcasting demands that only a single viewpoint be shown, at any particular time. This viewpoint is necessarily a compromise and is typically designed to displease the fewest number of viewers. We propose to create a new viewing paradigm which will take advantage of recent and emerging methods in computer vision, virtual reality and computer graphics technology, together with the computational capabilities likely to be available on next generation machines and networks. This new paradigm will allow each viewer the ability to view the field from any arbitrary viewpoint -- from the point of view of the ball headed toward the soccer goal; or from that of the goalie defending the goal; as the quarterback dropping back to pass; or as a hitter waiting for a pitch. In this way, the viewer can observe exactly those portions of the game which most interest him, and from the viewpoint that most interests him (e.g. some fans may want to have the best view of Michael Jordan as he sails toward the basket; others may want to see the world from his point of view). We propose developing a prototypical system which will allow each observer to view whatever he finds most exciting and interesting.


Project proposal

INFO 

Our First Meeting: An Overview

RELATEDWORK 

Very neat scheme for finding 3D shapes by controlling illumination
Combining Shape from Shading with Stereo for Surface reconstruction
CMU Virtualized Reality
UCSD MPI-Video
U. Wisconsin View Synthesis by Image Interpolation
U. Wisconsin View Morphing
Stanford Light Field Rendering
Microsoft Graphics Research (See Lumigraph)
Oxford work on tracking using condensation:
Work at U. Illinois on Shape Reconstruction:

DATASETS 

MIT AI Lab VVR Datasets

DATASHEETS 

Data sheet for the Brooktree chip in our framegrabbers






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Paul A. Viola ( viola@ai.mit.edu)
AI Lab Webmaster ( webmaster@ai.mit.edu)
Jeremy S. De Bonet ( jsd@ai.mit.edu)
Artificial Intelligence Laboratory
Massachusetts Institute of Technology
545 Technology Square (MIT NE43)
Cambridge, Massachusetts 02139
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